Visualization of finite element data of a multi-phase concrete model

M. Ritter1, M. Aschaber1, W. Benger2, G. Hofstetter1

1 University of Innsbruck, Austria2 Louisiana State University, USA

10.7.2013, Vienna

Center for Comput-ation and Technology ASTRO@

UIBK

• Outline– Motivation– Numerical Simulation– Data Modeling– Visualization– Conclusion & Future Work

• Motivation:

by Neal Stone

Scientific Visualization Techniques and

Research

Engineering Simulation Tools and Visualization

Gap

Motivation

• Motivation:

by Neal Stone

Scientific Visualization Techniques and

Research

Engineering Simulation Tools and Visualization

Motivation

• Motivation:• Simulation techniques are used more frequently• Produced data sets growing• Data complexity is increasing

• Visualization used for data interpretation of results is important.

Motivation

Numerical Simulation

10.7.2013, Vienna

• Aim:– More realistic simulation of drying shrinkage

• Application:– Strengthening of a RC structure by adding an overlay

Numerical Simulation

New top concrete layer

Old concrete structure

• Drying shrinkage:– Long term drying process in concrete– Decrease of relative pore humidity– Increase of capillary pressure– Capillary pressure results in volumetric shrinkage

Numerical Simulation

concrete

drying

• Drying Shrinkage:

Numerical Simulation

New top concrete layer

Old concrete structure

Different internal stresses Critical region at joint

Drying shrinkage

Swelling

concrete

• Numerical Simulation:– Finite element simulation on multiple grids of

concrete specimen– Hexahedral Mesh of 9 x 9 x 13 Cells

Numerical Simulation

100 x 100 x 56 mm

• Numerical Simulation:– Finite element simulation on multiple grids of

concrete specimen– Hexahedral Mesh of 9 x 9 x 13 Cells

Numerical Simulation

Undeformed linear element Deformed quadratic elementThe element has curved faces

• Multiphase concrete model• Solid, water, and gas phase

(dry air and water vapor)• Coupled hygral-thermo-mechanical

model

Numerical Simulation:

• Balance equations• Mass • Enthalpy• Linear Momentum

• Linear kinematic relations• Constitutive equations

Governing equations:

Numerical Simulation

Multiple solution variables (Data fields)• Gas pressure scalar• Capillary pressure scalar• Displacements vector• Temperature scalar

Derived data fields• Strain 2nd order tensor• Stress 2nd order tensor

• Drying shrinkage – Effective stress:

– Hydrostatic pressure of the water on the solid phase:

Numerical Simulation

Data Modeling

10.7.2013, Vienna

Before doing data visualization one has to deal with data• Many different kinds• Many formats

Data management and handling is crucial in computational sciences• Reusability of methods and techniques• Sustainability• Exchangeability of data (collaborations)

We propose using a concept based on mathematics to systematically organize data

Data Modeling

Separation of Geometry (Grids) and Datafield (Fields)

Inspired by concepts of:Topology Differential Geometry Geometric Algebra

Fiber Bundle Data Model

Grid

Field

Data Modeling

• Manifold describing the base space• Topology• Refinement level• Coordinate representation• Vertex positions in representation• Neighborhood

Gridthe base space

Data Modeling

• Dataset holding numerical data • per k-cell on the grid (vertex, edge, cell, … )• Array of arbitrary type, for example:

• Scalar• Vector, BiVector, …• Tensor• Any other user defined type

Fieldthe fiber

space

Data Modeling

Data Modeling

• Hierarchical structure:

Supported Grid types:• Uniform Grid• Curvilinear Grid• Rectilinear Grid• Adaptive Mesh Refinement Grid (AMR)• Point Cloud• Lines• Triangular/Quad and Mixed Surfaces

Grids can be fragmented (Blocks) having Ghost Zones

Grids can have refinement levels

Work in progress:• Hexahedral Grid• FEM Grid• Connected Graph Data• Full Waveform LIDAR Laser Data

Data Modeling

Fiber: 0D 1D 3D 6D BA

SE:

3D

2D

1D

0D

Data Modeling

Data Modeling

• Data at Vertices:

T=0.0 FE-Mes h

PointsCarte s ian

Pos itions PointDis placement VectorPre s s ure Scalar

<3 x double><3 x double><double>

Ce llsCe lls AsPoints

Pos itions Indice s<8 x uns igned long>

Stre s s Av Tens or<6 x double>( )

S tre s s Av Tens or<8 x <6 x double> >( )

(optional)

(optional)

Data Modeling

• Data at Integration Points:

T=0.0 FE-Mes h_IP

PointsCarte s ian

Stre s s Te ns or<6 x double >Ce lls

Ce lls As PointsPos itions Indice s<8 x uns igne d long>

No positions can be computed

Data Modeling

• Sets of Nodes and Sets of Elements:

T=0.0 FE-Me s h

PClus te rPClus te rAs Points

Pos itions<uns igne d long>

CClus te rCClus te rAs Ce lls

Pos itions

PName 1

<uns igne d long>CName1<uns igne d long>CName2

Indices of vertices in named fragments

Indices of integration pointsin named fragments

Data Modeling

• Linked groups for alternative data access:– E.g. time frames and time steps in ABAQUS

No data stored

T=0.0 Bundle - frames

T=0.2 T=0.4 T=0.6 T=0.8 T=1.0 T=1.2 T=1.4

T=0.0 Bundle - s teps

T=1.0 Link

Link

Data Modeling

HDF5 Based Data format: independent, free, open, data browserwww.hdfgroup.org

FEM - Example

Visualization

10.7.2013, Vienna

• Visualization framework• Highly modular design

– Small Core – Plug-Ins

• Mainly developed by Werner Benger– Currently about 8 people are actively contributing

• C++, OpenGL• Open Academic License• Runs on Linux, Windows (and MacOS)• http://vish.fiberbundle.net

Visualization Shell VISH

Visualization

Visualization

Data handling

• Based on the fiber bundle concept

• Allows to implement highly reusable visualization modules

Visualization

• Colored Cages– Show FE grid

• Positive• Negative

– Shaded colored surface– Illustrates data at vertices– One scalar field via color-map– One vector field via displacement– Can be combined with other visualization

techniques

Visualization

• Colored Cages– Integration point data is extrapolated and averaged on demand

Visualization

Extrapolation from integration points

Averaged,smoothed

Over-scaled deformation

• Tensor analysis:– Shape factors by [Westin97]– Stress/strain are 3x3 symmetric tensors– 3 Eigen-Values:

– Shape factors:

[BBHKS06]

Visualization

• Direct stress tensor visualization:– Ellipsoids representing the shape factors– Tensor Splats [BengerHege04]

-> barycentric

Visualization

• Direct stress tensor visualization:– Ellipsoids representing the shape factors– Tensor Splats [BengerHege04]

-> barycentric

Visualization

Works only for positive Eigenvalues!

• Direct stress tensor visualization:– Ellipsoids representing the shape factors– Tensor Splats [BengerHege04]

-> barycentric[BBHKS06]

Visualization

Works only for positive Eigenvalues!

Enhancement:Color a splat in blue, when any Eigenvalues is negative

Visualization

• Drying simulation:– Tensor splats:

Biaxial tension

Uniaxial tension

Pressure region

+ Multiple stress directions+ Tension vs pressure regions

• Scalar fields by volume rendering:– Texture based volume rendering ( requires resampling on

uniform grid to be improved)– Shows inner structure of data fields– Example: tri-axial compression of a cuboid

Visualization

and Mises in ABAQUS and Mises via volume rendering

• Drying simulation:– After 30 days of drying– Volume rendering of drying shrinkage – Cages show an uplift of the corner and the edges

• Dual volume rendering:– One scalar field controls color– Another controls transparency

Conclusion &Future Work

10.7.2013, Vienna

Fiber bundle data model for FEM• Captures many other types of scientific data• Comes with an HDF5 based data format (big data)

Good for collaborations and transparent data storage

Visualization:• Colored cages • Direct tensor field visualization• Scalar fields via volume rendering• Dual volume rendering

Future work:• Enhancing the direct tensor field visualization• Volume rendering on the FEM grid (GPU raycasting)• Support more FEM data (also shells)

-The END-

10.7.2013, Vienna

• Balance equations of the multiphase modelMass of the water w

Mass of the steam gw

Mass of the dry air ga

Mass of the solid phase s

Enthalpy of the whole system

Impulse of the whole system

Numerical Simulation